EventHallusion: Diagnosing Event Hallucinations in Video LLMs

Understand

Recently, Multimodal Large Language Models (MLLMs) have made significant progress in the video comprehension field.

• Despite remarkable content reasoning and instruction following capabilities they demonstrated, the hallucination problem of these VideoLLMs is less explored compared with its counterpart in the image domain.
• To mitigate this gap, we propose EventHallusion, a novel benchmark that focuses on assessing the VideoLLMs' hallucination toward event, the crux of video analysis.
• From a hallucination attribution perspective, our EventHallusion benchmark is curated to assess a VideoLLM's susceptibility toward language priors and vision-language biases.